Gold price prediction by a CNN-Bi-LSTM model along with automatic parameter tuning.

ABSTRACT: Banking and stock markets consider gold to be an important component of their economic and financial status. There are various factors that influence the gold price trend and its fluctuations. Accurate and reliable prediction of the gold price is an essential part of financial and portfolio management. Moreover, it could provide insights about potential buy and sell points in order to prevent financial damages and reduce the risk of investment. In this paper, different architectures of deep neural network (DNN) have been proposed based on long short-term memory (LSTM) and convolutional-based neural networks (CNN) as a hybrid model, along with automatic parameter tuning to increase the accuracy, coefficient of determination, of the forecasting results. An illustrative dataset from the closi

SUBMITTER: Amini A 

PROVIDER: S-EPMC10919698 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature